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Dioptra (acquired by Icertis) Tech Stack

AI agent for contract analysis, negotiation, and management

Technology, Information and Media New York, NY 2–10 employees Founded 2021 Privately Held

Dioptra builds legal AI agents focused on contract workflows—analysis, redlining, negotiation support, and obligation tracking. The founding team combines AI research backgrounds with over a decade of hands-on contracting and legal-ops experience each. The tech stack (Python, TypeScript, React, OpenAI, Anthropic, LangGraph, CrewAI, AutoGen) reflects a multi-model AI architecture, suggesting deliberate choices around LLM reliability rather than single-vendor lock-in.

Tech Stack 13 technologies

Core StackJavaScript TypeScript React Python Cursor OpenAI Anthropic SQL Git Codex LangGraph CrewAI AutoGen

What Dioptra (acquired by Icertis) Is Building

◆Challenges

Scaling to new customers

▲Active Projects

Contract operating system
Ai agent technology

Hiring Activity

Minimal6 roles · 0 in 30d

Department

Engineering

6

Seniority

Lead

4

Senior

2

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About Dioptra (acquired by Icertis)

Dioptra is a contract intelligence platform built by founders with deep expertise in both AI systems and commercial contracting operations. The company focuses on the full contract lifecycle—from initial analysis through obligation management—using AI agents rather than traditional document-processing tools. Founded in 2021 and headquartered in New York, Dioptra operates as a lean engineering organization scaling to serve enterprise legal and procurement teams.

HeadquartersNew York, NY

Company Size2–10 employees

Founded2021

Hiring MarketsUnited States, Canada

Frequently Asked Questions

What AI models does Dioptra use?

Dioptra integrates OpenAI and Anthropic models alongside orchestration frameworks like LangGraph, CrewAI, and AutoGen, indicating a multi-model approach rather than reliance on a single LLM provider.

What tech stack does Dioptra use?

Core languages are Python and TypeScript; frontend uses React. AI orchestration relies on LangGraph, CrewAI, and AutoGen. The stack emphasizes agentic AI patterns and multi-model LLM integration.

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